Efficient fingerprint-based user authentication for embedded systems.

User authentication, which refers to the process of verifying
the identity of a user, is becoming an important security requirement
in various embedded systems. While conventional
solutions for user authentication have relied on password-based
mechanisms, they are increasingly being replaced by biometric
technologies such as fingerprint, face, and voice recognition,
which are known to provide higher levels of security
for user authentication. This paper investigates the problem
of supporting efficient fingerprint-based user authentication
in embedded systems. For improving the performance of
fingerprint-based authentication, we propose hardware/software
enhancements that include a generic set of custom instruction
extensions to an embedded processor’s instruction set architecture,
a memory-aware software re-design, and fixed-point
arithmetic. We believe that the custom instruction set extensions
proposed in this work are generic enough to speed up
many fingerprint matching algorithms and even other biometric
algorithms. Our experiments with an open-source, highfidelity
fingerprint authentication algorithm and a testbed featuring
a commercial extensible processor show that performance
is improved by a factor of 10.4X when using the proposed
enhancements, while incurring modest overheads.